Ghorbel, Leïla and Zayani, Corinne Amel and Amous, Ikram and Sèdes, Florence
Semi-Supervised Algorithm with Knowledge-based Features for Learner's Profiles Interoperability.
(2018)
International Journal of Technology Enhanced Learning, 10 (1/2). 137-159. ISSN 1753-5255
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 950kB |
Official URL: https://www.doi.org/10.1504/IJTEL.2018.088343
Abstract
Nowadays, the user can have several profiles found in different adaptive systems relative to various fields. In particular, adaptive e-learning systems respond to a strong need to adapt to each learner their proposed activities based on the data stored in his/her profile (learning-style, interest, etc.). However, each system can have incomplete data as far as the learner is concerned. Hence, the exchange of the learner's profile data is extremely important in order to enhance his/her learning experience. The exchange requires a matching process so as to resolve the large number of a learner's profiles differences whether in syntax, structure or semantics. In this context, we propose a matching process to automatically detect the similarity between the profile elements. The originality of this process resides in the fact that it rests on a new semi-supervised Tri-Training algorithm which significantly improves the state of the art approaches.
Item Type: | Article |
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HAL Id: | hal-02562112 |
Audience (journal): | International peer-reviewed journal |
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Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE) Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE) Other partners > Université de Sfax (TUNISIA) |
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Statistics: | download |
Deposited On: | 29 Apr 2020 10:12 |
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